Robert Engle’s FT lectures on volatility, part 1

Some time ago (well, I guess the pre-crisis days of 2007 qualify as “some time ago”) Robert Engle, professor of finance and director of the Center for Financial Econometrics at NYU’s Stern School of Business as well as a Nobel Prize winner for his work on ARCH, gave a five-part “mini-course” on volatility on FT.com. The videos are, as far as I can ascertain, no longer available, but the transcripts are. However, the transcripts don’t include the graphics to which Engle refers.

As is my wonkish wont, I took notes on this series; more important, I saved the graphics. Their quality was poor in the original, and capturing them with HyperSnap, pasting them into a Word document, and then extricating them so I could paste them into this blog certainly didn’t improve matters. But fuzzy is better than nothing.

While I read the books I have here for review (including a 654-page tome on probability and statistics for finance which I am determined to implant in my brain) I plan to fill in the blanks by publishing my notes on these videos. Of course, for anyone who cares about this subject I highly recommend going to the original transcripts; they’re very brief and not at all technical, probably about two typed pages each.

And, although I think I gave the link to NYU Stern’s Volatility Laboratory earlier, here it is again. It “provides real time measurement, modeling and forecasting of financial volatility, correlations and risk for a wide spectrum of assets.” It’s decidedly beta, and I suspect always will be. Interesting nonetheless.

So, here are my notes on and the accompanying graphics from the first video.

The red graphic indicates the amplitude of volatility.

The periods when volatility is high are those when the market is in decline. When the market is going up, as in the middle 1990s, volatility is low. Actually, in the mid-1990s volatility was at a record low.

Volatility tends to mean revert. Indeed, in the late 90s volatility was very high, meaning that risk was high. And subsequently, of course, the market turned down. And we had high volatility as the market declined. 

What we are calculating in this chart is the standard deviation of the returns on an annualized basis from 1997 to 2003. Since the broad index has a lower volatility than its components you see the benefits of diversification. The highest volatility on this chart is small caps. Every piece of information that tells us whether this is an up and coming company or one that’s not going to make it is critical. This is the news theory.

This chart shows the median annual volatility of about 50 countries during the same period—1997 to 2003. The low vol countries are Chile, the UK, Australia, New Zealand, Austria, Canada, etc. The high vol countries are Turkey, Korea, Brazil, Finland, Russia, etc.